Computer-Implemented System And Method For Filtering An Information Space

ABSTRACT

A computer-implemented system and method for filtering an information space is provided. A collection of entities is accessed. Each entity is associated with one or more attributes defining characteristics of that entity. Multiple displays of the entity collection are generated and each display is based on a different attribute of the entity collection. A status is assigned to one or more entities in the collection and each status reflects progress of a user with respect to that entity. A visualization is assigned to each different assigned status and is reflected on each attribute display.

CROSS-REFERENCE TO RELATED APPLICATION

This patent application is a continuation of U.S. patent applicationSer. No. 13/866,926 filed Apr. 19, 2013, pending, the priority filingdate of which is claimed, and the disclosure of which is incorporated byreference.

This invention was made with government support under Contract No.2011-11090700005 CSS ProVisTasks 6. The government has certain rights inthe invention.

FIELD

This application relates in general to filtering information based onattributes and, in particular, to a computer-implemented system andmethod for filtering an information space.

BACKGROUND

Research is necessary to advance knowledge and is often conducted toincrease a user's understanding about a particular issue or topic.Currently, a majority of the research is conducted via the Web. However,conducting research can be time consuming, inefficient, and inaccuratedue to the large number of electronic documents available, which oftentimes cannot be read in their entirety.

Conventionally, users conduct research by entering a query, locatingresults that satisfy the query, and reviewing at least a portion of theresults, which are often provided as a list. For example, a user,writing a thesis paper on Prader-Willi syndrome, conducts researchrelating to the syndrome by identifying documents that mention or arerelated to the syndrome. Once accessed, the user can begin reviewing thedocuments, but is unable to determine how much of the material she hasaccessed with respect to the information space for Prader-Willisyndrome. Thus, the user must keep reading until he believes that he hascovered an adequate amount of material. One indication that may signalto the user that he has reviewed enough of the material is when the userstarts seeing some of the same material from different sources. Howeverinherent memory limits severely restrict the ability of the user to keepa mental map of the progress in addition to the knowledge extracted fromthe documents review.

Also, using conventional search methods, the user is unable to identifyhow much of the information space she has researched and thus, does notknow whether she should continue to conduct research or whether thedocuments she has accessed and reviewed are sufficient for covering theinformation on Prader-Willi. Accordingly, the current search tools failto provide a user with an overview of an information space or providethe user with means for tracking progress through that space andrecognizing when the topic has been sufficiently researched by the user.

Therefore, there is a need for providing tools that allow users to viewa search space for a topic and track review progress of that space.Preferably the tools are interactive so the user can perform a guidedfiltering of the result set down to a manageable list for review.

SUMMARY

An embodiment provides a computer-implemented system and method forfiltering an information space. A collection of entities is accessed.Each entity is associated with one or more attributes definingcharacteristics of that entity. Multiple displays of the entitycollection are generated and each display is based on a differentattribute of the entity collection. A status is assigned to one or moreentities in the collection and each status reflects progress of a userwith respect to that entity. A visualization is assigned to eachdifferent assigned status and is reflected on each attribute display.

Still other embodiments of the present invention will become readilyapparent to those skilled in the art from the following detaileddescription, wherein is described embodiments of the invention by way ofillustrating the best mode contemplated for carrying out the invention.As will be realized, the invention is capable of other and differentembodiments and its several details are capable of modifications invarious obvious respects, all without departing from the spirit and thescope of the present invention. Accordingly, the drawings and detaileddescription are to be regarded as illustrative in nature and not asrestrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram showing a computer-implemented system forexploring and filtering an information space based on attributes via aninteractive display, in accordance with one embodiment.

FIG. 2 is a flow diagram showing a method for exploring and filtering aninformation space based on attributes via an interactive display, inaccordance with one embodiment.

FIG. 3 is a screenshot showing, by way of example, a visual interfacefor displaying entities and visualizations of the entities.

FIG. 4 is a screenshot showing, by way of example, a visual interfacewith an entity view.

FIG. 5 is a screenshot showing, by way of example, a visual interfacewith a thematic view.

FIG. 6 is a screenshot showing, by way of example, a visual interfacefor filtering entities.

DETAILED DESCRIPTION

Exploring an information space using conventional search tools can betime-consuming and frustrating due to the large amounts of informationthat can be obtained. During review, a user is unable to determine howmuch of a particular information space she has covered since the currentsearch engines display the results as lists of documents that can belisted on multiple pages. Further, the conventional search tools fail toprovide any assistance in weeding through the often times numerousresults. Interactive filter tools allow a user to visualize aninformation space, review entities in the information space, identifythose entities most important for review, and determine which part ofthe information space to review next.

The filter tools are used within an interactive display for presentingthe results. FIG. 1 is a block diagram showing a computer-implementedsystem for exploring and filtering an information space based onattributes via an interactive display, in accordance with oneembodiment, in accordance with one embodiment. The system can operatevia a cloud computing environment, which allows end users to access andutilize remotely-stored applications 49 without requiring the users toinstall software or personal data. Instead, clients receive cloud-basedsoftware 13 and stored data. Each of the end users operate computingdevices 17-20, including a desktop computer 20, laptop 17, tablet 19, orcellular telephone 18, as well as other types of computing devices, toaccess the applications 13 and data 15, 16 stored on remote servers 12and databases 14, respectively, via a network 11. At a minimum, eachcomputing device should include accessibility to an internetwork andhave the ability to execute an application.

The user device 17-20 and servers 12 include components conventionallyfound in general purpose programmable computing devices, such as acentral processing unit, memory, input/output ports, network interfaces,and non-volatile storage, although other components are possible.Moreover, other information sources in lieu of or in addition to theservers, and other information consumers, in lieu of or in addition touser devices, are possible.

Once accessed, the application 13 allows the user to visualize aninformation space, filter the information set, and track her progressthrough the information. The information space can include a pluralityof entities that are each associated with one or more attributesdefining characteristics of that entity and can also includerelationships amongst the plurality of entities. An entity can includedocuments, movies, insurance claims, cars, patents, photographs, andsocial networking updates, such as statuses or tweets. Other types ofentities are possible. For instance, an information space can cover“movies,” while the individual entities can be particular movies, suchas “Big,” “You've Got Mail,” “Can't Buy Me Love,” “The Temple of Doom,”“The Wood” and many others.

At a minimum each entity should be associated with one or moreattributes. For example, news articles are associated with attributesfor publication source, author, topic, date published and others,whereas movie attributes include director, actors, genre, release dateand others. The entities can be obtained via a search by the user or byaccessing stored information, such as in a database. The user caninteract with the entities via an interface on the user devices.

The user device 17-20 and servers 12 can include one or more modules forcarrying out the embodiments disclosed herein. The modules can beimplemented as a computer program or procedure written as source code ina conventional programming language and is presented for execution bythe central processing unit as object or byte code. Alternatively, themodules could also be implemented in hardware, either as integratedcircuitry or burned into read-only memory components. The variousimplementations of the source code and object and byte codes can be heldon a computer-readable storage medium, such as a floppy disk, harddrive, digital video disk (DVD), random access memory (RAM), read-onlymemory (ROM) and similar storage mediums. Other types of modules andmodule functions are possible, as well as other physical hardwarecomponents.

Interactive Display

The interactive display allows a user to visualize the information spaceand narrow the results for review appropriately. FIG. 2 is a flowdiagram showing a method for exploring and filtering an informationspace based on attributes via an interactive display, in accordance withone embodiment. Entities associated with an information space areaccessed (block 41) based on instructions from a user. For instance, auser can conduct a search for information and the entities are providedas results of the search. Additionally, the information space can beaccessed from storage, such as a database. Multiple visualizations ofthe entities are generated (block 42) and can include an entity list,attribute graphs, and an entity view. Each visualization can representthe entities based on a particular attribute, such as source of theentity, date associated with the entity, and user status with respect tothat entity. The different types of visualizations are described indetail below with reference to FIG. 3. Other visualizations arepossible, such as a thematic display, as further described below withreference to FIG. 4.

The entity visualizations are presented (block 43) to a user via aninteractive display. Once presented, the user can interact with theentities in the particular information space by marking one or more ofthe entities with a status (block 44) or by selecting the entitiesdisplayed within one of the visualizations (block 45). Once marked, atleast one of the other visualizations is updated (block 46) to reflectthe user markings. Entity statuses are further discussed below withreference to FIG. 3.

The user can interact with the entities of a particular attribute typewithin a particular information space via a visual layout. FIG. 3 is ascreenshot showing, by way of example, an interface 50 for displayingentities and visualizations of the entities. The interface 50 caninclude an order field 52, entity list 51 and attribute graphs 54.

Entity List

The entities presented in the list can include all entities associatedwith an information space or those entities identified as results of asearch conducted by a user. The user can select to order the listedentities by relevance, date, or source, as well as by other attributes,by selecting an appropriate box in the document order field 52. In theexample with reference to FIG. 3, the entities are documents that arepart of an information space regarding “mortgage.” Each entity, ordocument, displayed in the list can be associated with an identifier,such as a title, a date, a source, a brief summary, a status 135, athumbnail 136, and a relevance bar 137.

The thumbnail 56 can be an image of the entity or an image of arepresentation of the entity. For instance, when the entity is adocument, a first page of the document can be displayed. Alternatively,a movie can be represented by a movie poster, which is displayed as thethumbnail.

Entity Triage

A user can perform entity triage by assigning a status, such as “toread,” “important,” “read,” or “unread” to one or more entities, ordocuments, in the list 53. Other statuses are possible, such as“irrelevant,” “save,” or “send to.” For instance, the user can click ona check box to the right side of the document header to toggle betweendifferent statuses. The system can also assign certain status statesautomatically, such as marking an entity as “read” when the user selectsthat entity with a pointer device or “unread” when the user assigns nostatus to that entity. Statuses can also include sub-categories, such aspriority levels on entities marked as “to read,” or reasons why anentity is marked with a particular status, such as “important.”Additionally, a combination of user assignments and default assignmentscan be used to identify particular entities as unread or read. Eachstatus can be represented by a different color or other marking, such astext, patterns, or symbols. Document triage allows the user to easilyidentify which entities she has reviewed, not yet reviewed, or plans toreview.

Entity Attribute Graphs

The entity attributes graphs 54 can be located adjacent to the entitylist 51 to provide an overview of the entities within the list, and caninclude a date histogram 58, source histogram 59, and status histogram60. Other attributes are possible, including author and cited works fordocument entities; producer and actor for movie entities; and cost andtype for car entities. As well, other types of graphs can be used torepresent the entity attributes, such as a pie chart, line graph, map,or word cloud. In the example, with reference to FIG. 3, the entitiesare documents and are represented by attribute graphs for date, source,and status. The date range histogram 58 is a zoomable visualization thatcan represent a hierarchy of variables, such as time ranges, includingminutes, hours, days, weeks, months, years, or longer. Other time rangesare possible. The time ranges can be set by pulling or contracting theends of the histogram line or through some other means, such as havingexplicit buttons to drive the zoom or GUI elements to specify a range.Each time period within the range is represented by a bar, and a lengthof the bar identifies a number of entities within the list 51 that werepublished, released during, or otherwise associated with that particulartime. A longer bar indicates more entities associated with thatparticular time, while a shorter bar indicates less entities. In anotherembodiment, the date bars represent the dates of events associated withthe entities.

The source histogram 59 includes one or more sources of the entities inthe list 51. The source can be an individual or organization thatpublished or released the entity or a representation of the entity. Forinstance, an organization can include variables for a news organization,an academic institution, a private company, or a department within anorganization. Alternatively, the source can include variables for amedium in which the entity was originally published, such as a book,newspaper, Website, magazine, video, or other medium. Additionally, thesource histogram can also be modified, such as by zooming in or out ofthe histogram, to display types of sources rather than individualsources. Other modifications of the histogram are possible, such asstretching and shortening the graph. The types of sources can includenews articles, scholarly articles, internal briefs, classifieddocuments, and so on. Other sources are possible. The user can selectwhich of the sources to display in the histogram, such as from a list.Each source listed in the histogram can be associated with a bar thatrepresents a number of entities associated with that particular source.Zoom capabilities, such as zoom-in and zoom-out, for the sourcehistogram can show a hierarchy of sources.

Meanwhile, the status histogram 60 can include the user's triageactivities indicating the entity statuses. The user status variables caninclude “unread,” “read,” “to read,” and “important.” Other statuses arepossible. The number of marked entities for each status is calculatedand used to determine a length of the bar for that status. The user canutilize the status histogram 60 to determine how she is progressingthrough the entities. In one embodiment, each status is assigned adifferent color to distinguish between the different statuses and thecolor can be applied to the bar for that status. For instance, a graycolor is assigned to an unread status, a blue color to a read status, agreen color to a to read status, and a red color to an important status.Other colors are possible.

The document list 51 and attribute graphs 54 are interrelated, such thata selection of an entity or attribute in one of the sections isreflected in the other section, as further described below withreference to FIG. 6.

Entity View

The user can analyze the entities in further detail by selecting one ofthe entities in the list for review. FIG. 4 is a screenshot showing, byway of example, an interface with an entity view. Upon selection, textand images associated with an entity can be displayed in a view section71 of the interface 150. At least a portion of the informationassociated with the entity can be displayed. However, in one embodiment,the entire entity or entire representation of the entity can be providedand the user can scroll through the displayed entity via a scrollbar.The scroll bar can include a movable bar 153 and a track 154.

Thematic View

The entities can be clustered by theme and presented in a display. FIG.5 is a screenshot showing, by way of example, a visuospatial searchinterface 80 with a thematic view. The thematic view can include a graphsection 81 that provides a visual display of clustered entities 83, asdescribed in commonly-owned U.S. Patent Application titled“Computer-Implemented System and Method for Visual Search Construction,Document Triage, and Coverage Tracking,” by Isaacs, filed on Apr. 19,2013, pending, the disclosure of which is hereby incorporated byreference. In the example with respect to FIG. 5, the entities aredocuments within an information space relating to the “mortgage crisis.”The entity list 51 includes all of the documents in the informationspace, which are clustered by at least one attribute of the entities. Inthis example, the documents are clustered by topics of the documents,including “Fannie Mae,” “Mortgage,” and “U.S. Housing Bubble.” Theclustered entities 83 are then displayed via a theme box in the graphsection 81. Each theme box can be represented by an icon or a shape,such as a square or circle, and can be associated with an identifier,such as a name of the topics. Other types of theme boxes are possible.Each of the documents can be associated with one or more topics.

The clustered entities 83 can be displayed randomly or in a particularorder, which can be selected by the user or as a default. In oneembodiment, those topic results that are highly related are placed nearone another in the graph, while the less related topics are locatedfurther apart.

In a further example, an information space for cars, which includesentities for make and model, can be grouped by manufacturer. Thus, atheme box would represent “Ford,” “Chevrolet,” “Honda,” “Toyota,”“Hyundai,” “Audi,” “Saab,” and so on. The entities represented by the“Honda” theme box could include “Civic,” “Accord,” “Pilot,” “Passport,”and “Odyssey,” as well as other models of Honda manufactured cars. In anadditional example, an information space for movies with individualmovies as entities, can be clustered based on genre, including romanticcomedy, comedy, horror, action, adventure, drama, fantasy, and sciencefiction. Other genres are possible. The entities can also be clusteredby other attributes associated with the entities. For instance, cars canbe clustered based on engine size or average miles per gallon, whilemovies can be clustered by producer, actor, or year.

The graph section 81 can also include a search field 82 so that a usercan conduct a search of the entities based on one or more attributes.For instance, based on the example of FIG. 5, the user may wish toidentify topics of entities having particular attributes. The userenters a query with search topics for “Subprime Mortgage Crisis” and“Subprime Crisis Impact Timeline.” The topics with entities that satisfythe search query are presented as search results, such that those topicsmost relevant to the query are located near a top of the entity graph 81and the topics less relevant are located further down the graph. Thelist of entities 51 can be updated to include only those entitiesassociated with the result topics displayed in the list. As well, theattributes graphs can be updated to include only the entities associatedwith the result topics.

Returning to the above movie example, the user wants to see the types ofmovies that the actor, “Tom Hanks” acted in during the 1980's. Theresults can include the genres of romantic comedy, comedy, and crime.The entities within the romantic comedy genre include “Big,” “Splash,”and “The Money Pit,” while the comedy genre includes “Dragnet,” “Nothingin Common,” and “Turner and Hooch.” Additionally, “Dragnet” and “Turnerand Hooch” are also grouped in the genre for crime. The entity list andattribute graphs are updated to include only those entities that areassociated with displayed genres in response to the search.

One or more clusters of entities in the entity graph 81 can be selectedby the user and the remaining clusters of entities that are related tothe selected entity cluster can be identified. The user can select theentity cluster 83 via a pointer device, such as a mouse, stylus, finger,or other type of pointer device. Specifically, the user can use thepointer device to hover over the topic box associated with the topic orto click or tap on the topic box. The related entity clusters 83 can beidentified by highlighting or color-coding the associated theme boxesbased on a relevance of that entity cluster 83 to the selected entitycluster 83. In one example, a color similar to a color of the selectedentity cluster 83 can be assigned to those entity clusters 83 having ahigher relevance to the selected entity cluster 83, while a differentcolor is assigned to entity clusters 83 that are less relevant. Othermethods for visualizing relatedness are possible, such as varying thedarkness of the color to show degree of relevance or using shape,perceived depth, font treatment, or animation, as well as patterns andicons. The relevance, or relatedness, of an entity cluster can bedetermined by comparing the entities associated with the selected entitycluster with the entities of each other entity cluster. The entityclusters with entities most related to the entities of the selectedentity cluster are selected as related entity clusters. In one example,the entities can be compared using cosine similarity. However, othermeans for determining relevance can be used.

Upon selection of a result topic, the documents in the list are alsoupdated to reflect only those documents that are associated with theselected result topic. As well, each of the document attribute graphs isalso updated to reflect the documents associated with the relevanttopics.

Entity Filtering

Filters can be applied to identify entities of interest. Any changes tothe entities based on the filters can also be applied to the otherentity visualizations, including the attribute graphs. FIG. 6 is ascreenshot showing, by way of example, a visual interface 90 forfiltering entities. The entities can be filtered based on one or more ofthe attributes associated with the entities, including date, source, orstatus. Other attributes are possible, including author and cited worksfor documents; producer and actor for movies; and cost and type forcars. However, in the following example, date, source, and statusfilters will be discussed with reference to document entities. The daterange 91 of all the entities in the list can be adjusted to display onlya subset of the entities that fall within a selected date range. Forexample, when the entities are documents, the documents can be organizedby publication date along the date histogram 58. The time range of allthe documents associated with the information space is from 1990 to2012. However, most of the documents occur later in time, from around2005 to 2012, with the years 2007 and 2008 having the most documentspublished. Thus, a user may want to focus more closely on the yearsduring which the most documents were published.

To filter the documents, the user can change the date range from 1990through 2012 to 2007 through 2008. Those documents published from 1990to 2006 and 2009 to 2012 are no longer represented by the date histogramand the same changes are made to the entity list and other attributegraphs, such that only those documents published between 2007 to 2008are represented by each display. The non-represented documents can beremoved from the display or can fade into the background, such as byreducing an intensity of the color or size. Other date filters can beused, such as months, days, or times. Additionally, since the time rangeof the date histogram is greatly reduced, each bar can now represent ashorter amount of time, such as a month, whereas the complete datehistogram from 1990 to 2012 used the bars to represent years. Otherexamples are possible. The other visualizations, including the entitylist and other attribute graphs can be updated to include only thosedocuments published during 2007 or 2008.

With respect to movies, the time can represent a date that a particularmovie was released. For instance, using the timeline in theabove-example, all entities associated with a date during the time rangefrom 1990 to 2012 are displayed in the entity list. The list can includemovies, such as “Can't Buy Me Love,” “The Dark Knight,” “Twilight,”“Wall-E,” “Die Hard,” “The Shawshank Redemption,” “The Godfather,” “Menin Black,” “Inception,” “Transformers,” “Ocean's Thirteen,” “CaptainAmerica: The First Avenger,” “The Hobbit,” and many others. To reducethe number of entities displayed and review only those entities from aparticular time period, the user can select a shorter time range, suchas from 2007 to 2008. Accordingly, the date histogram is updated toreflect only those movies that were released during 2007 and 2008,including, for instance, “The Dark Knight,” “Twilight,” “Wall-E,”“Transformers,” and “Ocean's 13.” The entity list and other attributegraphs are updated to include only the movies released during 2007 and2008.

The entities can also be filtered by source. A source histogram 59organizes entities associated with an information space by a publicationsource. The sources can include companies, journals, newspapers,universities, briefs, Web published documents, and books, as well asother sources, such as specific organizations, including the New YorkTimes (NYT), Associated Press (AP), Wall Street Journal (WSJ), Reuters,and Washington Post (WPost). In one example, the user can select tofurther research only those documents from particular sources, such asthe WSJ and WPost. Accordingly, documents published by the NYT, AP, andReuters can be removed or made less visible to the user by using alighter color of text. Additionally, the entity list and other attributegraphs can be updated to include or highlight only those documents thatwere published by the WSJ and WPost.

In the movie example, the source of the movies can refer to theproduction company that released the movies and can include ApolloPictures, Warner Brothers, Castle Rock Entertainment, Columbia PicturesCorporation, Dream Works SKG, Paramount Pictures, New Line Cinema, andTwentieth Century Fox Film Corporation, as well as many other productioncompanies. The user can select one or more of the production companies,such as Warner Brothers and Paramount Pictures and those movies, such as“The Dark Knight” and “Inception,” produced by Warner Brothers and“Captain America: The First Avenger” and “The Godfather,” produced byParamount Pictures are filtered for inclusion in the source histogram,while the remaining movies not produced by Warner Brothers or ParamountPictures can be removed from the graph. The list of entities and otherattribute graphs are updated to include only those movies from WarnerBrothers and Paramount Pictures.

The status filter can be used to identify a portion of the displayedentities in the list that are marked with a particular status by theuser. The user statuses can include “unread,” “read,” “to read,” and“important.” When the entities are documents, the status histogram 60can be used to organize the documents of the by user status. In oneexample, the user may wish to review all the documents that she hasmarked as “to read.” The “to read” documents can be selected byselecting the bar associated with the “to read” status of the statushistogram 60 with a pointer device. The documents with a “to read”status remain displayed in the entity list, while the documents withother statuses are removed from the display or visually reduced so thatthe “to read” documents are more visibly displayed. The remainingattribute graphs are updated to include only those documents that areassociated with the selected user status.

With regards to the movie example, the different statuses can include“watch,” “to watch,” “not interested in watching,” and “recommended byfriends.” The user can select one or more of the statuses to filter theentities and identify only those entities that are associated with oneof the selected statuses. The entity list and attribute graphs areupdated to include only those entities with the selected statuses.

Additionally, the user can apply filters to two or more of the entityattributes to identify entities that satisfy the filters for eachattribute. For instance, a user may wish to review all those documententities that she has read and that were published in 2008. To apply thefilters, the user can identify the bar associated with the year 2008 andselect the color blue, which is associated with the “read” status, usinga pointer device. Accordingly, based on the filters, the date histogram,source histogram, and entity list can be updated to display only thosedocuments published in 2008 that were read by the user.

During the user's review of the entities, she may identify an entitythat is not of interest. The user can elect to remove the entity byselecting a menu option (not shown) for deleting or hiding that entity.Upon removal of the entity, the interactive system learns which entitiesare not relevant to the user and updates the entity list and attributegraphs.

Additionally, at any point during the user's review of the entities, shecan place a pointer device over any portion of the histograms to reflecta sub-region 91 of the graph in higher resolution to be able to see thesmall status markings easily. Additionally, a display of a graphsub-region can be used by the user to select a portion of one of thehistogram bars associated with a variable. For example, the user canopen a pop up window 91 by hovering his pointer device over the datehistogram to display in further detail the months of May, June, and July2008. The pop up window displays the month variables 91 in greaterdetail so that a user can filter the entities by selecting a user statusdisplayed on one of the bars, such as those documents published duringJune 2008 that the user has read. The read documents of June 2008 can beindicated by a color or a symbol, including dark stripes over arepresentation of the read entities for the June variable.

Coverage Tracking

A user can easily track her research using the statuses assigned to oneor more entities. Specifically, the user can also track her status withrespect to review of the entities using the attribute graphs. Forinstance, a user can see how many entities are associated with aparticular status, date, or source, as well as other attributes. Whenthe entities are documents, a user status of the documents can bereflected on the attribute graphs, including the date histogram andsource histogram, to indicate how much material the user has covered bysource and time. With regards to the date histogram, the user statusescan be displayed by applying an appropriate status color to the bars ofthe histogram. For example, with reference to FIG. 5, the year 2008 inthe date histogram 58 is associated with a longest bar indicating theyear during which the most documents were published. If 400 documentswere published in 2008 and the user has read 20 of the documents, then alength of the bar is colored purple to indicate the amount of documentsread by the user that were published in 2008. Specifically, the portionof the bar that is colored purple is proportionate to the number ofdocuments read. Thus, 5%, or 1/20, of the bar for 2008 would be coloredpurple. Also, in this example, the user has marked 50 documents with a“to read” status, which is 12.5% of the total documents for 2008. Thus,12.5% of the bar is shaded, or colored, green to indicate a portion ofthe documents published in 2008 that the user intends to read. The colorgreen can be applied adjacent to the color red for read documents.

The order in which the user statuses are displayed along each bar can beselected by the user, implemented as a default, or can be arbitrary.Other colors or markings to indicate user status are possible. The userstatuses can be similarly applied to the source histogram 139 toindicate a user's progress of reviewing documents organized by source.Color coding the source histogram with user status can assist a user inidentifying how much material she has covered with respect to documentspublished by a certain source.

As a user assigns a status to one of the documents in the list, thestatus is also reflected in the status histogram and the status bar ofthe topic results. Tracking the user's status allows that user to seehow many of the documents associated with the result topics she hascovered, either by reading the full document, a portion of the documentor a summary of the document. The user can then use the trackedinformation to determine how much more of the material she needs toreview to get a good understanding of the information surrounding thetopics of the search query.

Returning to the movie example, the user can track how many movies shehas seen in each genre, in each year of release, from each productioncompany, as well as based on other attributes. The user can also use thetracking information to learn something, such as the type of movies shelikes or an era of movies. For instance, if the user has seen lots ofmovies released between 1980 to 1990 and they are mostly romanticcomedies, the user may determine that romantic comedies are herfavorite, as well as the time. The user can then easily find othermovies that have the same attributes or at least one of the attributes.For instance, the user may just determine that she likes movies releasedduring the 80's and may want to look for movies released in the 80'sthat are classified as action.

Coverage tracking also allows a user to determine any biases she mayhave with respect to particular entities. For instance, with respect tothe document example, the user may determine that she has not reviewedany documents published prior to 2008 since she was so focused on thehousing crisis that she forgot to review earlier documents.Additionally, the user can use the tracking to focus her researchregarding an information space by determining how many documents she hasreviewed with respect to the different attributes. For instance, theuser may not realize that she has only viewed documents published by theWall Street Journal and Washington Post and thus, should begin reviewingdocuments from the other sources. Also, returning to the mortgagedocument example, the user can easily identify all documents relating tomortgages and then track her progress through the documents using thedate histogram. Based on the statuses applied to the date histogram, theuser identifies that she has disproportionately reviewed the documents,with most of her review focused on documents before the housing crisis.Accordingly, the properly cover the information space, the user shouldstart reviewing documents that were published during the housing crisisto cover this important period in time relating to housing mortgages.

Although the above examples focus on documents and movies, otherentities are possible, including cars, patents, photographs, andinsurance claims. At a minimum each entity should be associated with oneor more attributes, which can be used to filter the entities and trackthe user's review of the entities.

While the invention has been particularly shown and described asreferenced to the embodiments thereof, those skilled in the art willunderstand that the foregoing and other changes in form and detail maybe made therein without departing from the spirit and scope of theinvention.

What is claimed is:
 1. A computer-implemented system for filtering aninformation space, comprising: a collection of entities, each entityassociated with one or more attributes defining characteristics of thatentity; a display module to generate multiple displays of the entitycollection, each display based on a different attribute of the entitycollection; a status assignment module to assign a status to one or moreentities in the collection, wherein each status reflects progress of auser with respect to that entity; a visualization assignment module toassign a visualization for the assigned statuses; and a presentationmodule to reflect the assigned visualizations of the assigned statuseson each attribute display.
 2. A system according to claim 1, furthercomprising: a receipt module to receive at least a portion of thestatuses from the user; and an update module to update the displays withthe received statuses.
 3. A system according to claim 1, furthercomprising: an automatic assignment module to automatically assign atleast a portion of the statuses.
 4. A system according to claim 3,wherein the statuses are automatically assigned based on an actionperformed by the user.
 5. A system according to claim 1, wherein thestatuses include sub-categories comprising one or more of prioritylevels and reasons for assigning the user statuses.
 6. A systemaccording to claim 1, wherein the assigned visualizations are reflectedon each display by counting a number of entities assigned for eachdifferent status, determining a size of representation for that statusin the display, and displaying the visualization for that status withinthe representation.
 7. A system according to claim 1, furthercomprising: an access module to obtain the entity collection via asearch query.
 8. A system according to claim 1, further comprising: afilter module to filter the entities by receiving one of the userstatuses from the user and displaying the entities assigned with thereceived user status.
 9. A system according to claim 1, furthercomprising: a filter module to filter the entities based on at least oneof the user statuses and the attributes.
 10. A system according to claim1, further comprising: an entity display module to display a list of oneor more of the entities, each entity associated with an icon of theentity and the assigned status.
 11. A computer-implemented method forfiltering an information space, comprising: accessing a collection ofentities, each entity associated with one or more attributes definingcharacteristics of that entity; generating multiple displays of theentity collection, each display based on a different attribute of theentity collection; assigning a status to one or more entities in thecollection, wherein each status reflects progress of a user with respectto that entity; further assigning a visualization to the assignedstatuses; and reflecting the assigned visualizations of the assignedstatuses on each attribute display.
 12. A method according to claim 11,further comprising: receiving at least a portion of the statuses fromthe user; and updating the displays with the received statuses.
 13. Amethod according to claim 11, further comprising: automaticallyassigning at least a portion of the statuses.
 14. A method according toclaim 13, wherein the statuses are automatically assigned based on anaction performed by the user.
 15. A method according to claim 11,wherein the statuses include sub-categories comprising one or more ofpriority levels and reasons for assigning the user statuses.
 16. Amethod according to claim 11, wherein the assigned visualizations arereflected on each display, comprising: counting a number of entitiesassigned for each different status; determining a size of representationfor that status in the display; and displaying the visualization forthat status within the representation.
 17. A method according to claim11, further comprising: obtaining the entity collection via a searchquery.
 18. A method according to claim 11, further comprising: filteringthe entities, comprising: receiving one of the user statuses from theuser; and displaying the entities assigned with the received userstatus.
 19. A method according to claim 11, further comprising:filtering the entities based on at least one of the user statuses andthe attributes.
 20. A method according to claim 11, further comprising:displaying a list of one or more of the entities, each entity associatedwith an icon of the entity and the assigned status.